This application addresses broad Challenge Area (06): Enabling Technologies and specific Challenge Topic, 06-DC-101: Develop Improved Hearing Devices. It is projected that by 2030 there will be over 40 million adults and over 2 million children with hearing loss in the United States. The average reduction in earning potential for individuals with hearing aids is estimated to be $11,500 per year and $23,000 per year for individuals with untreated hearing loss. Total annual lost income of American workers with hearing loss is enormous. An important variable influencing these figures is hearing aid performance, especially in noise. Advancements in hearing aid performance have the potential to improve quality of life for more than 10 percent of the American population as well as productivity the average hearing- impaired worker. The challenge in advancing hearing aid performance is to overcome the blurring, or distortion, of frequency information important for understanding speech caused by damage to the inner ear. Distortion in the inner ear is the reason why making speech louder does not always make it clearer. In fact, amplification can contribute further to the distortion. Current hearing aid strategies compress, or squeeze, the amplitude and/or frequency range of speech in order to provide listeners with greater access to information, particularly the softer parts and higher frequency parts of speech. The full ability to improve speech understanding with these strategies is limited by the fact that they, too, increase blurring of the speech signal. The signal processing strategy proposed here, the Contrast Enhancement (CE) algorithm, sharpens the contrast in the speech signal in order to minimize effects of the blur caused by the damaged inner ear. The CE algorithm is efficient and operates in real time, so it is ideal for hearing aid applications. Innovative aspects of the CE algorithm include simulation of biological processes that are important for understanding connected speech, especially processes that operate across successive speech sounds to enhance signature changes in their frequency composition. The CE algorithm is currently very successful in restoring speech understanding in normal-hearing individuals listening to speech that is blurred to simulate inner ear damage. Further improvements to the CE algorithm will be investigated using normal-hearing listeners with simulated inner ear damage. The CE algorithm also will be tested for improving speech understanding for people who have a wide range of different hearing losses. These tests with hearing impaired listeners include an innovative approach to customizing the algorithm for individual hearing losses. While the CE algorithm might work well as a standalone processing strategy, there are strong reasons to believe that its greatest and most immediate impact will occur when used together with current signal processing strategies already used in hearing aids. As noted above, some of these methods tend to increase the blur in the speech signal. Therefore, using a wide range of listeners with different types of hearing loss, the effectiveness of the CE algorithm will be tested for reducing the negative consequences of current processing strategies so that overall speech understanding is improved. Finally, the CE algorithm has the potential to help cochlear implant users who experience a severe form of blurring in the speech signal. Like hearing aid users, blurring with electrical hearing is attributable both to impaired inner ear functioning and to device processing that is necessary to accommodate the impairment. As a result of the blurring, cochlear implant users cannot make full use of information in the electrical patterns representing the speech signal. The objective is to exploit the CE algorithm so that current and future cochlear implant users will be able to take greater advantage of the information in their implants. Effectiveness of the CE algorithm will first be tested using normal-hearing listeners with simulated cochlear implant processing. Next, benefits of contrast-enhanced speech on word and sentence recognition will be tested using actual cochlear implant recipients. Proposed research is to refine and implement signal processing strategies that improve performance of hearing aids and cochlear implants in order to provide better hearing and quality of life to millions of Americans with hearing impairments.